Magnetic microrobots have become an emerging field because they are less invasive in biomedicine and easy to pass through a narrow environment.However

it is still a challenge to design autonomous navigation control systems for microrobots in complex environments.An autonomous navigation control scheme for microrobots based on microscopic visual feedback is proposed.Firstly

a semantic segmentation model is designed to build a global semantic map under the microscope.Then

RRT-connect path planning algorithm is improved and a trajectory tracking control model based on reinforcement learning are designed to follow the planned path.Finally

an experimental platform is setup to conduct an experiment of autonomous navigation of a magnetic microrobot.The result proves that the solution can construct a global semantic map in a complex environment

and realize path planning and navigation control.